BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures

BNPmix is an R package for Bayesian nonparametric multivariate density estimation, clustering, and regression, using Pitman-Yor mixture models, a flexible and robust generalization of the popular class of Dirichlet process mixture models. A variety of model specifications and state-of-the-art poster...

Full description

Bibliographic Details
Main Authors: Riccardo Corradin, Antonio Canale, Bernardo Nipoti
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2021-11-01
Series:Journal of Statistical Software
Subjects:
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/3867
Description
Summary:BNPmix is an R package for Bayesian nonparametric multivariate density estimation, clustering, and regression, using Pitman-Yor mixture models, a flexible and robust generalization of the popular class of Dirichlet process mixture models. A variety of model specifications and state-of-the-art posterior samplers are implemented. In order to achieve computational efficiency, all sampling methods are written in C++ and seamless integrated into R by means of the Rcpp and RcppArmadillo packages. BNPmix exploits the ggplot2 capabilities and implements a series of generic functions to plot and print summaries of posterior densities and induced clustering of the data.
ISSN:1548-7660